# nltk/nltk_data

NLTK Data

Repository: https://github.com/nltk/nltk_data
Canonical: https://ross.abutalabs.com/products/nltk_data
Language: Python
License: Apache-2.0
License Family: permissive
Topics: nltk, nlp, natural-language-processing, corpora, linguistics
Last push: 2026-07-01T00:40:19+00:00

## Health v2 (maintenance only)
Score: 73/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 90, release rhythm 35, longevity 100
- inputs: {"age_days": 5228, "days_push": 64, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1827, forks 1088 (observed 2026-08-28T04:05:41.565648+00:00)

## What it is
The official data distribution repository for NLTK, containing corpora, trained models, tokenizers, and other data packages used with the Natural Language Toolkit. Data is installed via NLTK's built-in downloader (nltk.download()).

## Use cases
- download corpora for nltk text processing
- get tokenizer models for sentence and word splitting
- find labeled datasets for nlp teaching and experiments
- obtain pretrained models for pos tagging and named entity recognition
- set up nltk data for a python nlp project
- access stopwords and wordnet for text preprocessing

## When to choose
- you use NLTK and need its corpora, grammars, or trained models
- you want well-known reference datasets for NLP education and prototyping

## When to avoid
- you need a modern deep-learning model hub rather than classic NLP data
- you require strict licensing guarantees without checking per-dataset terms, since individual package licenses vary

## Facets
- artifact type: dataset
- maturity: stable
- function: nlp, machine-learning
- domain: data-science
- platform: python, cross-platform
- tags: corpora, tokenizers, nltk, language-models, text-data, natural-language-processing, linguistics

## Member repositories
- nltk/nltk_data (main) score 73

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:05:41.565648+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T03:19:25.888186+00:00, confidence not recorded.
  - readme: https://github.com/nltk/nltk_data (fetched 2026-08-28T04:05:41.565648+00:00, sha c15eb1477201)
- Data as of 2026-08-30T08:39:29.467469+00:00.